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The Cleveland Clinic Lerner of College of Medicine of Case Western Reserve University (CCLCM) is a five-year program dedicated to developing the next generation of physician investigators. Students are assigned dedicated physician and research advisors to help ensure they reach their goals. In their fourth year, students work with a mentor to develop a master’s-level thesis in basic science, translational medicine, clinical medicine or health systems. When the students graduate, they each receive an MD with Special Qualification in Biomedical Research from Case Western Reserve University.
The research in which students are involved is critical, timely and often results in presentations at national conferences and publication in scholarly journals. The examples below briefly describe two students’ research projects, one that involves using machine learning to maximize benefits of genetic testing for those with chronic kidney disease, and another that involves addressing a gap in care for those with diabetic kidney disease:
"For my master's thesis, I defended a project titled ‘Utilization of Predictive Modeling to Maximize the Benefits of Genetic Testing for Patients with Chronic Kidney Disease.’ Genetic testing is increasingly important to diagnose and manage kidney diseases but remains underused in practice. One barrier is provider uncertainty in determining which patients are likely to benefit from genetic evaluation. To address this barrier, we built a model to classify genetic testing outcomes based on readily available demographic, clinical and laboratory data to serve as a clinical decision support tool.
“Our model was trained on de-identified data from a cohort of about 700 patients evaluated by the Cleveland Clinic Renal Genetics Clinic with completed genetic testing from December 2018 through May 2024. We used machine learning (artificial intelligence) to understand the complex interactions between predictor variables, then explicitly modeled these relationships using interaction terms in a logistic regression framework. More simply put, we used machine learning tools to improve the performance and reliability of our logistic regression model. We were successful in building a model that accurately classifies genetic testing outcomes about 76% of the time (ROC-AUC 0.76). The next step in this project will be to validate model performance in a larger cohort of kidney disease patients not already referred for genetic testing.”
-Chloe Borden (’26)
“During my thesis year, I was awarded a fellowship through the Sarnoff Cardiovascular Research Foundation, which allowed me to conduct research at Emory University School of Medicine. This program is designed to prepare future physician-scientists through hands-on research and mentorship. Under the guidance of Modele Ogunniyi, MD, and Priyathama Vellanki, MD, I focused on improving access and care for patients with diabetes who develop kidney disease. This severe complication affects one in three adults with diabetes, leading to heart-related death and kidney failure. A newer class of medications, called sodium-glucose cotransporter-2 inhibitors (SGLT2i), is protective of both the kidneys and the heart, slowing kidney disease progression and reducing heart-related risk factors; however, they are not being prescribed as often as guidelines recommend.
“To better understand this gap in care, we analyzed one of the largest national datasets to date, including over 1.58 million adults with diabetic kidney disease (DKD), to identify patient-specific demographic and clinical factors that affect SGLT2i prescribing. We found that only half of eligible patients were receiving these guideline-recommended medications. Prescribing patterns were multifaceted, with differences based on age, sex, insurance status, race and even neighborhood-level social factors (e.g., economic stability and community resources), which influenced prescription status. My research highlights key opportunities to improve care for patients who would benefit from these life-sustaining medications. To optimize the equitable implementation of these therapies across the DKD population, targeted interventions addressing policy barriers, healthcare infrastructure, provider education and social support services are urgently needed.”
-Claudia Walker (’26)
